Dear Applied Statistics Community,
This Wednesday the Applied Statistics Workshop will welcome Matthew Harding,
Dept. of Economics, Stanford University. Matthew will be presenting his
research, "A Bayesian Mixed Logit-Probit Model for Multinomial Choice", a
project that is joint with Jerry Hausman and Michael Burda. Here is an
abstract for the presentation:
In this paper we introduce a new flexible mixed model for multinomial
discrete choice where the key individual- and alternative-specific
parameters of interest are allowed to follow an assumption-free
nonparametric density specification while other alternative-specific
coefficients are assumed to be drawn from a multivariate normal
distribution. A hierarchical specification of our model allows us to break
down a complex data structure into a set of submodels with the desired
features that are naturally assembled in the original system. We estimate
the model using a Bayesian Markov Chain Monte Carlo technique with a
multivariate Dirichlet Process (DP) prior on the coefficients with
nonparametrically estimated density. We bypass a problem of prior
non-conjugacy by employing a "latent class" sampling algorithm for the DP
prior. The model is applied to supermarket choices of a panel of Houston
households whose shopping behavior was observed over a 24-month period in
years 2004-2005. We estimate the nonparametric density of two key variables
of interest: the price of a basket of goods based on scanner data, and
driving distance to the supermarket based on their respective locations,
calculated using GPS software. Supermarket dummies form the parametric part
of our model.
The workshop meets at 12 noon with a light lunch and presentations usually
begin at 1215. Our workshop is located at 1737 Cambridge St, CGIS-Knafel,
room N-354.
Please contact me with any questions
Justin Grimmer
Dear Applied Statistics Community,
This Wednesday, 2/20, the applied statistics workshop welcomes Jim
Snyder, Arthur
and Ruth Sloan Professor of Economics and Political Science at MIT. He will
be presenting "The Wealth of Political Office in the US, 1840-1870" work
that is joint with Pablo Querubin, Department of Economics, MIT. Jim
provided the following abstract and the attached article:
The second half of the 19th century was known as a corrupt era in U.S.
politics. Using the censuses of 1850, 1860 and 1870, we find the wealth of
all candidates running for the U.S. House of Representatives during the
period 1840-1870. We use this data to estimate several quantities of
interest, including: How wealthy were these candidates compared to others
in the population at the time? How did the wealth accumulation of these
candidates compare to others in the population? How did the wealth levels
and accumulation vary by party? How did those candidates who won a
congressional race by a close margin compare with those who lost by a close
margin? This last quantity, which exploits a regression-discontinuity
approach, provides a good estimate of the monetary ``rents'' to a
congressional seat at that time.
As always, the workshop will convene at 12 noon with a light lunch and the
presentation will begin at 1215. We are located in CGIS-Knafel, 1737
Cambridge St, room N-354.
Please Contact me with any questions
Cheers
Justin Grimmer
Dear Applied Statistics Community,
This Wednesday the applied statistics workshop presents Donald Rubin --
Department of Statistics, Harvard University – who will present, "Direct and
Indirect Causal Effects: An unhelpful distinction?" Don has suggested the
following papers provide a helpful background to his talk:
2003 - "Assumptions Allowing the Estimation of Direct Causal Effects:
Discussion of `Healthy,
Wealthy, and Wise? Tests for Direct Causal Paths Between Health and
Socioeconomic
Status' by Adams et al.'". Journal of Econometrics, 112, pp. 79-87. (With F.
Mealli.)
2004 - "Direct and Indirect Causal Effects Via Potential Outcomes." The
Scandinavian Journal of
Statistics, 31, pp. 161-170; 196-198, with discussion and reply
"Causal Inference Using Potential Outcomes: Design, Modeling, Decisions."
2004 Fisher
Lecture. The Journal of the American Statistical Association, 100, 469, pp.
322-331.
The workshop meets at 12 noon in room N-354 CGIS-Knafel (1737 Cambridge St)
with a light lunch, with presentations usually beginning at 1215.
Please send along any comments or concerns
Cheers
Justin
Dear Applied Statistics Community,
Apologies for the late email this week—we've experienced some last minute
scheduling changes. This week Kevin Quinn, Department of Government, will
present 'Assessing Political Positions of Media' a project that is joint
with Daniel Ho, Stanford Law School. Kevin provided the following abstract:
Although central to understanding the role of the media, few quantitative
measures of the
political positions of media exist. We amass a new, large-scale dataset to
shed light on this question. Collecting and classifying over 1500 editorials
adopted by 25 major U.S. newspapers on 495 Supreme Court cases from
1994-2004, we apply an item response theoretic approach to place newspapers
on a substantively meaningful and long validated scale of political
preferences. Our results provide significant insights into the study of the
media. We show that 18 of the 25 papers are more likely to the left of the
median Justice for this period, but also considerable evidence that this may
be an artifact of the liberalness of urban, elite, high circulation papers.
Kevin also provided a link to the paper, which is available here:
http://www.people.fas.harvard.edu/~kquinn/papers/Ho_Quinn_unblind.pdf<http://www.people.fas.harvard.edu/%7Ekquinn/papers/Ho_Quinn_unblind.pdf>
Our workshop will convene this Wednesday at 12 noon with a light lunch, with
the presentation to start at 1215. We are located in CGIS-Knafel (1737
Cambridge St) Room N-354.
Please Contact me with any questions, comments, or concerns
Justin Grimmer